Intelligent colocation of HPC workloads

FV Zacarias, V Petrucci, R Nishtala, P Carpenter… - Journal of Parallel and …, 2021 - Elsevier
Many HPC applications suffer from a bottleneck in the shared caches, instruction execution
units, I/O or memory bandwidth, even though the remaining resources may be underutilized …

Online machine learning for energy-aware multicore real-time embedded systems

JLC Hoffmann, AA Fröhlich - IEEE Transactions on Computers, 2021 - ieeexplore.ieee.org
In this article, we present an Online Learning Artificial Neural Network (ANN) model that is
able to predict the performance of tasks in lower frequency levels and safely optimize real …

A review on shared resource contention in multicores and its mitigating techniques

PN Jain, SK Surve - International Journal of High …, 2020 - inderscienceonline.com
Chip multiprocessor (CMP) systems have become inevitable to meet high computing
demands. In such systems sharing of resources is imperative for better resource utilisation …

[PDF][PDF] Comparative Analysis on Various CSS and JavaScript Frameworks.

TK Mohd, J Thompson, A Carmine, G Reuter - J. Softw., 2022 - academia.edu
Web development is a huge part of the current world, affecting all parts of the world and
human interaction. Learning about frameworks used in web development allows for …

Software performance prediction at source level

EW Hu, B Su, J Wang - 2017 IEEE 15th International …, 2017 - ieeexplore.ieee.org
Performance prediction is critical in embedded system design for reducing the turnaround
time of software. Using simulation to measure the performance of the whole source code is …

Performance models for heterogeneous systems applied to the dark silicon-aware design space exploration

MT dos Santos, R Sonohata, C Krebs… - 2019 31st …, 2019 - ieeexplore.ieee.org
The design of computing systems requires tools for modeling, configuration, and simulation
of multiple architectural parameters and their interconnections. Simulators provide estimated …

A Fault Injection Framework for Real-time Multicore Embedded Systems

LP Horstmann, AA Fröhlich - 2020 X Brazilian Symposium on …, 2020 - ieeexplore.ieee.org
In this paper, we present a non-intrusive framework to inject faults in real-time multicore
embedded systems without impairing the temporal characteristics of the critical tasks being …

[PDF][PDF] Exploiting Data-Parallelism on Multicore and SMT Systems for Implementing the Fractal Image Compressing Problem.

R da Rosa Righi, VF Rodrigues… - Comput. Inf …, 2017 - pdfs.semanticscholar.org
This paper presents a parallel modeling of a lossy image compression method based on the
fractal theory and its evaluation over two versions of dual-core processors: with and without …

Using machine learning techniques for performance prediction on multi-cores

JK Rai, A Negi, R Wankar - International Journal of Grid and High …, 2011 - igi-global.com
Sharing of resources by the cores of multi-core processors brings performance issues for the
system. Majority of the shared resources belong to memory hierarchy sub-system of the …

Machine learning based performance prediction for multi-core simulation

JK Rai, A Negi, R Wankar - … -disciplinary Trends in Artificial Intelligence: 5th …, 2011 - Springer
Programs co-running on cores share resources on multi-core processor systems. It is now
well known that interference between the programs arising from the sharing may result in …